Biochemical networks can be described in terms of their elementary chemical reactions. Modeling of the specific reaction mechanisms within a given network allows us to predict and analyze how the network will respond to changing conditions. This knowledge can lead to finer manipulation of biochemical networks. From a biochemical industry perspective, this could translate to increased production rates of products such as biofuels, while from a research perspective this could expose primary targets for inhibition or promotion of malignant or benevolent networks, respectively. Biochemical networks are configured with feedback controls which allow them to respond to external fluctuations (such as increased output demand). These controls function by suppressing or enhancing enzyme activities, thereby regulating a specific reaction rate. Neighboring reactions adjust to compensate for the altered flux, until the network reaches a new steady state. In networks of any significant complexity, it is difficult to pinpoint the influence of any one feedback control on the network as a whole. The aim of this project is to analyze the network flux influence of specific feedback controls, and determine which control has the greatest flux influence in various biochemical networks. Our methods involve the use of the roadRunner biochemical network simulation library (sysBio, Seattle, WA). We will be using the library to analyze a large sample (20,000+) of instances of specific biochemical networks. Each instance will feature randomized chemical rate constants for each reaction in the network, with a fixed overall network equilibrium constant. We will simulate each network and record the flux control coefficients (sensitivities) of each reaction in the network. We will then compile our results and analyze the distribution of flux control coefficients vs. reaction. This will allow us to pinpoint which reaction(s) in a network exhibit the greatest influence on overall network flux.

The Systems Biology Markup Language (SBML) is a standard for representing models of biochemical reaction networks; it encourages model reuse and enables models to be analyzed by almost two hundred existing software tools that recognize it. In support of this standard, a number of software libraries have been contributed by Frank Bergman at the University of Washington, to enable model networks to be drawn in bitmap, vector graphics, and Portable Document Format (PDF). These libraries make it easier to display what is happening inside any particular model, automatically parsing model data and drawing molecules, cell compartments, and structures together with their relevant reactions from the model’s SBML file. The work described here extends these capabilities to the LaTeX document preparation system. All graphical information encoded in the model is transformed into vector graphics script that can be embedded in LaTeX documents. Once the document is compiled these scripts are translated into images. This is useful for both researchers and authors using LaTeX, enabling them to conveniently generate scalable vector graphics in their publications to diagram the biochemical models they have used or seek to explain. The extension is also available as a software library and can be embedded into other programs to enable them to export their models in LaTeX form.

When studying cellular networks computationally, visualizing the networks on screen can be a useful aid to the researcher. Currently, there are a handful of programs that exist for this purpose. They are all desktop applications that need to be installed on the computer before they can be used. One of the most common programs found on computers is the Internet browser and its prevalence makes it an interesting backbone on which to build a visualization tool. When building an application in a browser, the installation process can be avoided and differences in varying operating systems can be disregarded. A standard browser plug-in is Adobe’s Flash. The purpose of this study is to develop and evaluate Flash as the platform on which to build a web based pathway modeling tool. Using ActionScript (the programming language used to create Flash programs), I assessed the ability of Flash to create, edit and save representations of cellular networks in a simple and efficient manner. The application can form a pathway by listening to user events or by reading an input file. Once created, these pathways can be saved in three different formats: JPEG image, text file, and Systems Biology Markup Language. The ActionScript language fosters rapid graphical user interface development and offers many unique features with its library of classes. ActionScript has many built-in features; in particular, the process of creating visible objects and listening to user events has been streamlined. CS4 Professional, the environment used to write ActionScript code, is an integral part of the programming experience. It enables programmers to easily create readable code, pinpoint errors and publish their work in websites. In this study, Flash was found to be an exceptional platform for making this type of modeling tool.

Synthetic biology is a new and growing field of study where existing organisms are engineered at the DNA level. This project investigates the use of fusion proteins in synthetic biology research. Such proteins involve the fusion to two different proteins where one of the proteins is often a fluorescently active protein such as Green Fluorescent Protein (GFP) so that the fused protein can be easily tracked using light microscopy. The project will use fusion protein technology to monitor the level of enzymes in vivo. As a result the fusion protein will be used as a tool for research and provide valuable data to help re-engineering metabolic pathways. In this project, fusion proteins from enzymes (such as Phosphoglucoisomerase - PGI) found in the glycolytic pathway will be designed. In addition, the use of standardized biological parts will be explored in creating the genetic circuit that will control the fusion protein once in the cell. To design such a “gene circuit”, PCR (Polymerase Chain Reaction) and In-Fusion Assembly will be used once the PGI gene sequence is located on the chromosome. The In-Fusion method is a more efficient technique of connecting two different gene parts together than the traditional method of restriction digests. After creating the gene circuit on a plasmid, it will be inserted into the native chromosome of E.coli using an isogenic construction method, which allows one to insert the circuit at a precise point in the E.coli genome. Finally, the transformed E.coli will be tested using fluorescent microscopy where we expect to observe the glycolytic enzyme levels in the metabolic pathway as the organism grows.